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相关概念视频

Observational Learning01:12

Observational Learning

213
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
213
Associative Learning01:27

Associative Learning

452
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
452
Reinforcement01:23

Reinforcement

282
Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
282
Introduction to Learning01:18

Introduction to Learning

478
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
478
Purposive Learning01:22

Purposive Learning

146
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
146
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.8K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
1.8K

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相关实验视频

Updated: Jul 24, 2025

The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents
09:01

The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents

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在深度强化学习中转移学习:一项调查

Zhuangdi Zhu, Kaixiang Lin, Anil K Jain

    IEEE transactions on pattern analysis and machine intelligence
    |July 4, 2023
    PubMed
    概括

    本调查探讨了深度强化学习 (DRL) 中的转移学习 (TL). 我们对最先进的TL方法进行分类,以提高DRL在复杂任务中的效率和有效性.

    科学领域:

    • 人工智能的人工智能
    • 机器学习 机器学习
    • 深度学习 (Deep Learning) 是一种深度学习.

    背景情况:

    • 强化学习 (RL) 是顺序决策的一个关键范式.
    • 深度神经网络已经显著提升了RL的能力.
    • 在RL效率和有效性方面的挑战需要知识转移.

    研究的目的:

    • 系统地调查最近转移学习对深度强化学习的进展.
    • 为分类最先进的转移学习方法提供一个框架.
    • 分析DRL中转移学习的目标,方法,骨干和应用.

    主要方法:

    • 文献审查和转移学习技术的系统分类.
    • 基于定义的标准进行转移学习方法的分析.
    • 探索与相关RL主题和未来挑战的联系.

    主要成果:

    • 一个全面的框架,以了解转移学习在DRL.
    • 各种转移学习方法及其应用的分类.
    • 确定当前的局限性和未来的研究方向.

    结论:

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    • 转移学习对于推进深度强化学习至关重要.
    • 需要进一步的研究来应对挑战并释放充分的潜力.
    • 这项调查为DRL的研究人员和从业人员提供了宝贵的资源.